Overview

Dataset statistics

Number of variables17
Number of observations184
Missing cells655
Missing cells (%)20.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory136.7 B

Variable types

Numeric5
Text7
Categorical1
DateTime3
Unsupported1

Alerts

airdate has constant value ""Constant
id_embedded is highly overall correlated with seasonHigh correlation
season is highly overall correlated with id_embeddedHigh correlation
number is highly overall correlated with typeHigh correlation
type is highly overall correlated with numberHigh correlation
type is highly imbalanced (79.9%)Imbalance
number has 9 (4.9%) missing valuesMissing
airtime has 150 (81.5%) missing valuesMissing
runtime has 15 (8.2%) missing valuesMissing
rating_average has 184 (100.0%) missing valuesMissing
medium has 98 (53.3%) missing valuesMissing
original has 98 (53.3%) missing valuesMissing
summary has 101 (54.9%) missing valuesMissing
id has unique valuesUnique
url has unique valuesUnique
_links_self has unique valuesUnique
rating_average is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-08-05 19:15:59.136661
Analysis finished2023-08-05 19:16:02.963220
Duration3.83 seconds
Software versionydata-profiling vv4.4.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIQUE 

Distinct184
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2459313.5
Minimum2286565
Maximum2607221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:03.052179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2286565
5-th percentile2411052.4
Q12439664
median2449309.5
Q32458373.2
95-th percentile2571941.5
Maximum2607221
Range320656
Interquartile range (IQR)18709.25

Descriptive statistics

Standard deviation48009.611
Coefficient of variation (CV)0.01952155
Kurtosis2.9900815
Mean2459313.5
Median Absolute Deviation (MAD)9814.5
Skewness1.1691089
Sum4.5251369 × 108
Variance2.3049228 × 109
MonotonicityNot monotonic
2023-08-05T14:16:03.222839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2575561 1
 
0.5%
2443164 1
 
0.5%
2454115 1
 
0.5%
2456637 1
 
0.5%
2454063 1
 
0.5%
2445812 1
 
0.5%
2442735 1
 
0.5%
2457882 1
 
0.5%
2451856 1
 
0.5%
2397088 1
 
0.5%
Other values (174) 174
94.6%
ValueCountFrequency (%)
2286565 1
0.5%
2327475 1
0.5%
2393545 1
0.5%
2394195 1
0.5%
2395105 1
0.5%
2397088 1
0.5%
2397826 1
0.5%
2399223 1
0.5%
2403500 1
0.5%
2410540 1
0.5%
ValueCountFrequency (%)
2607221 1
0.5%
2607220 1
0.5%
2607219 1
0.5%
2607218 1
0.5%
2604311 1
0.5%
2603385 1
0.5%
2577831 1
0.5%
2575562 1
0.5%
2575561 1
0.5%
2572525 1
0.5%

id_embedded
Real number (ℝ)

HIGH CORRELATION 

Distinct122
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56284.821
Minimum81
Maximum70186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:03.390888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile19797.8
Q152750
median62737
Q365713
95-th percentile68564.75
Maximum70186
Range70105
Interquartile range (IQR)12963

Descriptive statistics

Standard deviation14578.517
Coefficient of variation (CV)0.25901329
Kurtosis3.5568621
Mean56284.821
Median Absolute Deviation (MAD)4530
Skewness-1.9241686
Sum10356407
Variance2.1253315 × 108
MonotonicityNot monotonic
2023-08-05T14:16:03.689226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53242 8
 
4.3%
50102 6
 
3.3%
67267 6
 
3.3%
65894 6
 
3.3%
58000 5
 
2.7%
65712 5
 
2.7%
70186 4
 
2.2%
65471 4
 
2.2%
55621 3
 
1.6%
65504 3
 
1.6%
Other values (112) 134
72.8%
ValueCountFrequency (%)
81 1
0.5%
4175 1
0.5%
5493 1
0.5%
6141 1
0.5%
13215 1
0.5%
13818 2
1.1%
16753 1
0.5%
17046 1
0.5%
19499 1
0.5%
21491 1
0.5%
ValueCountFrequency (%)
70186 4
2.2%
70093 1
 
0.5%
69351 1
 
0.5%
69238 2
1.1%
68784 1
 
0.5%
68639 1
 
0.5%
68144 1
 
0.5%
67907 1
 
0.5%
67883 2
1.1%
67776 1
 
0.5%

url
Text

UNIQUE 

Distinct184
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:03.938577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length132
Median length106
Mean length79.173913
Min length56

Characters and Unicode

Total characters14568
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2575561/hocu-vse-znat-2x91-seria-91
2nd rowhttps://www.tvmaze.com/episodes/2575562/hocu-vse-znat-2x92-seria-92
3rd rowhttps://www.tvmaze.com/episodes/2443145/manuna-2x01-seria-1
4th rowhttps://www.tvmaze.com/episodes/2443146/manuna-2x02-seria-2
5th rowhttps://www.tvmaze.com/episodes/2424821/s-nula-1x06-seria-06
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2575561/hocu-vse-znat-2x91-seria-91 1
 
0.5%
https://www.tvmaze.com/episodes/2410540/the-wonderland-of-ten-thousands-5x156-episode-332 1
 
0.5%
https://www.tvmaze.com/episodes/2443007/shining-just-for-you-1x17-episode-17 1
 
0.5%
https://www.tvmaze.com/episodes/2443145/manuna-2x01-seria-1 1
 
0.5%
https://www.tvmaze.com/episodes/2443146/manuna-2x02-seria-2 1
 
0.5%
https://www.tvmaze.com/episodes/2424821/s-nula-1x06-seria-06 1
 
0.5%
https://www.tvmaze.com/episodes/2417610/kungur-1x10-10-seria 1
 
0.5%
https://www.tvmaze.com/episodes/2440095/a-slezu-za-toboj-1x06-seria-6 1
 
0.5%
https://www.tvmaze.com/episodes/2445344/akter-1x03-seria-3 1
 
0.5%
https://www.tvmaze.com/episodes/2440050/the-director-who-buys-me-dinner-1x01-episode-1 1
 
0.5%
Other values (174) 174
94.6%
2023-08-05T14:16:04.392977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1258
 
8.6%
- 1137
 
7.8%
s 938
 
6.4%
/ 920
 
6.3%
t 878
 
6.0%
o 761
 
5.2%
w 626
 
4.3%
i 595
 
4.1%
a 583
 
4.0%
p 548
 
3.8%
Other values (30) 6324
43.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9901
68.0%
Decimal Number 2058
 
14.1%
Other Punctuation 1472
 
10.1%
Dash Punctuation 1137
 
7.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1258
12.7%
s 938
 
9.5%
t 878
 
8.9%
o 761
 
7.7%
w 626
 
6.3%
i 595
 
6.0%
a 583
 
5.9%
p 548
 
5.5%
m 510
 
5.2%
d 389
 
3.9%
Other values (16) 2815
28.4%
Decimal Number
ValueCountFrequency (%)
2 412
20.0%
1 342
16.6%
4 318
15.5%
0 231
11.2%
5 181
8.8%
3 174
8.5%
6 115
 
5.6%
9 109
 
5.3%
7 91
 
4.4%
8 85
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/ 920
62.5%
. 368
 
25.0%
: 184
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9901
68.0%
Common 4667
32.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1258
12.7%
s 938
 
9.5%
t 878
 
8.9%
o 761
 
7.7%
w 626
 
6.3%
i 595
 
6.0%
a 583
 
5.9%
p 548
 
5.5%
m 510
 
5.2%
d 389
 
3.9%
Other values (16) 2815
28.4%
Common
ValueCountFrequency (%)
- 1137
24.4%
/ 920
19.7%
2 412
 
8.8%
. 368
 
7.9%
1 342
 
7.3%
4 318
 
6.8%
0 231
 
4.9%
: 184
 
3.9%
5 181
 
3.9%
3 174
 
3.7%
Other values (4) 400
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1258
 
8.6%
- 1137
 
7.8%
s 938
 
6.4%
/ 920
 
6.3%
t 878
 
6.0%
o 761
 
5.2%
w 626
 
4.3%
i 595
 
4.1%
a 583
 
4.0%
p 548
 
3.8%
Other values (30) 6324
43.4%

name
Text

Distinct150
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:04.748892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length52
Mean length16.646739
Min length1

Characters and Unicode

Total characters3063
Distinct characters150
Distinct categories14 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)73.4%

Sample

1st rowСерия 91
2nd rowСерия 92
3rd rowСерия 1
4th rowСерия 2
5th rowСерия 06
ValueCountFrequency (%)
episode 61
 
10.6%
the 21
 
3.7%
2 10
 
1.7%
серия 10
 
1.7%
4 8
 
1.4%
1 8
 
1.4%
5 7
 
1.2%
aflevering 7
 
1.2%
to 7
 
1.2%
3 7
 
1.2%
Other values (348) 427
74.5%
2023-08-05T14:16:05.301180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389
 
12.7%
e 276
 
9.0%
i 166
 
5.4%
o 159
 
5.2%
s 135
 
4.4%
a 123
 
4.0%
t 109
 
3.6%
n 107
 
3.5%
r 99
 
3.2%
d 98
 
3.2%
Other values (140) 1402
45.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1931
63.0%
Uppercase Letter 505
 
16.5%
Space Separator 389
 
12.7%
Decimal Number 155
 
5.1%
Other Punctuation 57
 
1.9%
Other Letter 16
 
0.5%
Dash Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%
Other Number 1
 
< 0.1%
Initial Punctuation 1
 
< 0.1%
Other values (4) 4
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 276
14.3%
i 166
 
8.6%
o 159
 
8.2%
s 135
 
7.0%
a 123
 
6.4%
t 109
 
5.6%
n 107
 
5.5%
r 99
 
5.1%
d 98
 
5.1%
p 93
 
4.8%
Other values (51) 566
29.3%
Uppercase Letter
ValueCountFrequency (%)
E 94
18.6%
T 44
 
8.7%
S 35
 
6.9%
A 32
 
6.3%
L 24
 
4.8%
N 20
 
4.0%
M 19
 
3.8%
D 18
 
3.6%
I 17
 
3.4%
H 17
 
3.4%
Other values (37) 185
36.6%
Other Punctuation
ValueCountFrequency (%)
" 12
21.1%
' 10
17.5%
. 7
12.3%
, 7
12.3%
: 7
12.3%
! 5
8.8%
/ 3
 
5.3%
· 3
 
5.3%
& 1
 
1.8%
1
 
1.8%
Other Letter
ValueCountFrequency (%)
ل 3
18.8%
ا 3
18.8%
م 2
12.5%
ر 1
 
6.2%
د 1
 
6.2%
ي 1
 
6.2%
غ 1
 
6.2%
ب 1
 
6.2%
ح 1
 
6.2%
ق 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 34
21.9%
2 30
19.4%
3 17
11.0%
0 15
9.7%
4 14
9.0%
5 13
 
8.4%
6 11
 
7.1%
8 8
 
5.2%
9 7
 
4.5%
7 6
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
389
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 1
100.0%
Final Punctuation
ValueCountFrequency (%)
» 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2204
72.0%
Common 611
 
19.9%
Cyrillic 231
 
7.5%
Arabic 16
 
0.5%
Greek 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 276
 
12.5%
i 166
 
7.5%
o 159
 
7.2%
s 135
 
6.1%
a 123
 
5.6%
t 109
 
4.9%
n 107
 
4.9%
r 99
 
4.5%
d 98
 
4.4%
E 94
 
4.3%
Other values (47) 838
38.0%
Cyrillic
ValueCountFrequency (%)
и 25
 
10.8%
е 25
 
10.8%
р 18
 
7.8%
я 18
 
7.8%
о 12
 
5.2%
С 11
 
4.8%
а 11
 
4.8%
в 10
 
4.3%
н 8
 
3.5%
с 6
 
2.6%
Other values (40) 87
37.7%
Common
ValueCountFrequency (%)
389
63.7%
1 34
 
5.6%
2 30
 
4.9%
3 17
 
2.8%
0 15
 
2.5%
4 14
 
2.3%
5 13
 
2.1%
" 12
 
2.0%
6 11
 
1.8%
' 10
 
1.6%
Other values (21) 66
 
10.8%
Arabic
ValueCountFrequency (%)
ل 3
18.8%
ا 3
18.8%
م 2
12.5%
ر 1
 
6.2%
د 1
 
6.2%
ي 1
 
6.2%
غ 1
 
6.2%
ب 1
 
6.2%
ح 1
 
6.2%
ق 1
 
6.2%
Greek
ValueCountFrequency (%)
π 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2797
91.3%
Cyrillic 231
 
7.5%
Arabic 16
 
0.5%
None 16
 
0.5%
Punctuation 2
 
0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
389
 
13.9%
e 276
 
9.9%
i 166
 
5.9%
o 159
 
5.7%
s 135
 
4.8%
a 123
 
4.4%
t 109
 
3.9%
n 107
 
3.8%
r 99
 
3.5%
d 98
 
3.5%
Other values (64) 1136
40.6%
Cyrillic
ValueCountFrequency (%)
и 25
 
10.8%
е 25
 
10.8%
р 18
 
7.8%
я 18
 
7.8%
о 12
 
5.2%
С 11
 
4.8%
а 11
 
4.8%
в 10
 
4.3%
н 8
 
3.5%
с 6
 
2.6%
Other values (40) 87
37.7%
Arabic
ValueCountFrequency (%)
ل 3
18.8%
ا 3
18.8%
م 2
12.5%
ر 1
 
6.2%
د 1
 
6.2%
ي 1
 
6.2%
غ 1
 
6.2%
ب 1
 
6.2%
ح 1
 
6.2%
ق 1
 
6.2%
None
ValueCountFrequency (%)
· 3
18.8%
ä 2
12.5%
ó 2
12.5%
² 1
 
6.2%
« 1
 
6.2%
» 1
 
6.2%
π 1
 
6.2%
à 1
 
6.2%
é 1
 
6.2%
á 1
 
6.2%
Other values (2) 2
12.5%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.43478
Minimum1
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:05.459974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile27.1
Maximum2022
Range2021
Interquartile range (IQR)2

Descriptive statistics

Standard deviation436.72415
Coefficient of variation (CV)4.3054674
Kurtosis15.95561
Mean101.43478
Median Absolute Deviation (MAD)0
Skewness4.2166971
Sum18664
Variance190727.98
MonotonicityNot monotonic
2023-08-05T14:16:05.605714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 113
61.4%
2 22
 
12.0%
3 13
 
7.1%
2022 8
 
4.3%
4 5
 
2.7%
5 4
 
2.2%
13 2
 
1.1%
8 2
 
1.1%
6 2
 
1.1%
11 2
 
1.1%
Other values (10) 11
 
6.0%
ValueCountFrequency (%)
1 113
61.4%
2 22
 
12.0%
3 13
 
7.1%
4 5
 
2.7%
5 4
 
2.2%
6 2
 
1.1%
7 1
 
0.5%
8 2
 
1.1%
9 2
 
1.1%
10 1
 
0.5%
ValueCountFrequency (%)
2022 8
4.3%
2021 1
 
0.5%
28 1
 
0.5%
22 1
 
0.5%
19 1
 
0.5%
18 1
 
0.5%
17 1
 
0.5%
16 1
 
0.5%
13 2
 
1.1%
11 2
 
1.1%

number
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)26.3%
Missing9
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean21.211429
Minimum1
Maximum269
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:05.767968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q316
95-th percentile91.3
Maximum269
Range268
Interquartile range (IQR)12

Descriptive statistics

Standard deviation42.068989
Coefficient of variation (CV)1.9833171
Kurtosis16.950412
Mean21.211429
Median Absolute Deviation (MAD)4
Skewness3.9060225
Sum3712
Variance1769.7999
MonotonicityNot monotonic
2023-08-05T14:16:05.930356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
3 16
 
8.7%
2 14
 
7.6%
6 14
 
7.6%
4 14
 
7.6%
5 14
 
7.6%
1 12
 
6.5%
10 9
 
4.9%
7 9
 
4.9%
8 8
 
4.3%
13 5
 
2.7%
Other values (36) 60
32.6%
(Missing) 9
 
4.9%
ValueCountFrequency (%)
1 12
6.5%
2 14
7.6%
3 16
8.7%
4 14
7.6%
5 14
7.6%
6 14
7.6%
7 9
4.9%
8 8
4.3%
9 4
 
2.2%
10 9
4.9%
ValueCountFrequency (%)
269 1
0.5%
250 1
0.5%
242 1
0.5%
189 1
0.5%
156 1
0.5%
142 1
0.5%
132 1
0.5%
100 1
0.5%
92 1
0.5%
91 2
1.1%

type
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
regular
175 
significant_special
 
7
insignificant_special
 
2

Length

Max length21
Median length7
Mean length7.6086957
Min length7

Characters and Unicode

Total characters1400
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 175
95.1%
significant_special 7
 
3.8%
insignificant_special 2
 
1.1%

Length

2023-08-05T14:16:06.086823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-05T14:16:06.214464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 175
95.1%
significant_special 7
 
3.8%
insignificant_special 2
 
1.1%

Most occurring characters

ValueCountFrequency (%)
r 350
25.0%
a 193
13.8%
e 184
13.1%
g 184
13.1%
l 184
13.1%
u 175
12.5%
i 38
 
2.7%
n 20
 
1.4%
s 18
 
1.3%
c 18
 
1.3%
Other values (4) 36
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1391
99.4%
Connector Punctuation 9
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 350
25.2%
a 193
13.9%
e 184
13.2%
g 184
13.2%
l 184
13.2%
u 175
12.6%
i 38
 
2.7%
n 20
 
1.4%
s 18
 
1.3%
c 18
 
1.3%
Other values (3) 27
 
1.9%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1391
99.4%
Common 9
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 350
25.2%
a 193
13.9%
e 184
13.2%
g 184
13.2%
l 184
13.2%
u 175
12.6%
i 38
 
2.7%
n 20
 
1.4%
s 18
 
1.3%
c 18
 
1.3%
Other values (3) 27
 
1.9%
Common
ValueCountFrequency (%)
_ 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 350
25.0%
a 193
13.8%
e 184
13.1%
g 184
13.1%
l 184
13.1%
u 175
12.5%
i 38
 
2.7%
n 20
 
1.4%
s 18
 
1.3%
c 18
 
1.3%
Other values (4) 36
 
2.6%

airdate
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-12-15 00:00:00
Maximum2022-12-15 00:00:00
2023-08-05T14:16:06.317214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:06.432047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

airtime
Date

MISSING 

Distinct17
Distinct (%)50.0%
Missing150
Missing (%)81.5%
Memory size1.6 KiB
Minimum2023-08-05 00:00:00
Maximum2023-08-05 22:00:00
2023-08-05T14:16:06.546482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:06.691785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
Distinct25
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-12-15 00:00:00+00:00
Maximum2022-12-16 01:00:00+00:00
2023-08-05T14:16:06.840086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:06.977379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

runtime
Real number (ℝ)

MISSING 

Distinct56
Distinct (%)33.1%
Missing15
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean39.426036
Minimum1
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:07.125362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q121
median40
Q350
95-th percentile63
Maximum240
Range239
Interquartile range (IQR)29

Descriptive statistics

Standard deviation29.251915
Coefficient of variation (CV)0.74194413
Kurtosis17.055157
Mean39.426036
Median Absolute Deviation (MAD)15
Skewness3.1605398
Sum6663
Variance855.67456
MonotonicityNot monotonic
2023-08-05T14:16:07.290349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 17
 
9.2%
60 12
 
6.5%
25 9
 
4.9%
40 8
 
4.3%
20 8
 
4.3%
47 6
 
3.3%
26 5
 
2.7%
30 5
 
2.7%
53 5
 
2.7%
12 5
 
2.7%
Other values (46) 89
48.4%
(Missing) 15
 
8.2%
ValueCountFrequency (%)
1 1
 
0.5%
2 3
1.6%
3 2
 
1.1%
4 3
1.6%
5 1
 
0.5%
6 3
1.6%
7 1
 
0.5%
10 3
1.6%
11 2
 
1.1%
12 5
2.7%
ValueCountFrequency (%)
240 1
 
0.5%
180 1
 
0.5%
165 1
 
0.5%
120 2
 
1.1%
89 1
 
0.5%
66 1
 
0.5%
65 2
 
1.1%
60 12
6.5%
59 1
 
0.5%
58 2
 
1.1%

rating_average
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing184
Missing (%)100.0%
Memory size1.6 KiB

medium
Text

MISSING 

Distinct86
Distinct (%)100.0%
Missing98
Missing (%)53.3%
Memory size1.6 KiB
2023-08-05T14:16:07.523517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters6278
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/438/1095206.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/438/1095208.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/435/1087719.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/435/1087720.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/435/1087732.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/462/1155357.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/442/1105390.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/438/1095208.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/435/1087719.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/435/1087720.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/435/1087732.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/451/1129501.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/451/1129502.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/451/1129503.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/451/1129504.jpg 1
 
1.2%
Other values (76) 76
88.4%
2023-08-05T14:16:07.895787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 602
 
9.6%
a 516
 
8.2%
m 430
 
6.8%
s 430
 
6.8%
t 430
 
6.8%
p 344
 
5.5%
e 344
 
5.5%
i 258
 
4.1%
c 258
 
4.1%
. 258
 
4.1%
Other values (22) 2408
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4386
69.9%
Other Punctuation 946
 
15.1%
Decimal Number 860
 
13.7%
Connector Punctuation 86
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 516
11.8%
m 430
9.8%
s 430
9.8%
t 430
9.8%
p 344
 
7.8%
e 344
 
7.8%
i 258
 
5.9%
c 258
 
5.9%
d 258
 
5.9%
o 172
 
3.9%
Other values (8) 946
21.6%
Decimal Number
ValueCountFrequency (%)
1 130
15.1%
3 116
13.5%
4 110
12.8%
0 105
12.2%
8 103
12.0%
5 100
11.6%
9 65
7.6%
7 62
7.2%
2 36
 
4.2%
6 33
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 602
63.6%
. 258
27.3%
: 86
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4386
69.9%
Common 1892
30.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 516
11.8%
m 430
9.8%
s 430
9.8%
t 430
9.8%
p 344
 
7.8%
e 344
 
7.8%
i 258
 
5.9%
c 258
 
5.9%
d 258
 
5.9%
o 172
 
3.9%
Other values (8) 946
21.6%
Common
ValueCountFrequency (%)
/ 602
31.8%
. 258
13.6%
1 130
 
6.9%
3 116
 
6.1%
4 110
 
5.8%
0 105
 
5.5%
8 103
 
5.4%
5 100
 
5.3%
_ 86
 
4.5%
: 86
 
4.5%
Other values (4) 196
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 602
 
9.6%
a 516
 
8.2%
m 430
 
6.8%
s 430
 
6.8%
t 430
 
6.8%
p 344
 
5.5%
e 344
 
5.5%
i 258
 
4.1%
c 258
 
4.1%
. 258
 
4.1%
Other values (22) 2408
38.4%

original
Text

MISSING 

Distinct86
Distinct (%)100.0%
Missing98
Missing (%)53.3%
Memory size1.6 KiB
2023-08-05T14:16:08.148349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters6450
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/438/1095206.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/438/1095208.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/435/1087719.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/435/1087720.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/435/1087732.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/462/1155357.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/442/1105390.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/438/1095208.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/435/1087719.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/435/1087720.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/435/1087732.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/451/1129501.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/451/1129502.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/451/1129503.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/451/1129504.jpg 1
 
1.2%
Other values (76) 76
88.4%
2023-08-05T14:16:08.524688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 602
 
9.3%
t 516
 
8.0%
a 430
 
6.7%
s 344
 
5.3%
i 344
 
5.3%
o 344
 
5.3%
p 258
 
4.0%
c 258
 
4.0%
. 258
 
4.0%
g 258
 
4.0%
Other values (23) 2838
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4558
70.7%
Other Punctuation 946
 
14.7%
Decimal Number 860
 
13.3%
Connector Punctuation 86
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 516
 
11.3%
a 430
 
9.4%
s 344
 
7.5%
i 344
 
7.5%
o 344
 
7.5%
p 258
 
5.7%
c 258
 
5.7%
g 258
 
5.7%
m 258
 
5.7%
e 258
 
5.7%
Other values (9) 1290
28.3%
Decimal Number
ValueCountFrequency (%)
1 130
15.1%
3 116
13.5%
4 110
12.8%
0 105
12.2%
8 103
12.0%
5 100
11.6%
9 65
7.6%
7 62
7.2%
2 36
 
4.2%
6 33
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 602
63.6%
. 258
27.3%
: 86
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4558
70.7%
Common 1892
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 516
 
11.3%
a 430
 
9.4%
s 344
 
7.5%
i 344
 
7.5%
o 344
 
7.5%
p 258
 
5.7%
c 258
 
5.7%
g 258
 
5.7%
m 258
 
5.7%
e 258
 
5.7%
Other values (9) 1290
28.3%
Common
ValueCountFrequency (%)
/ 602
31.8%
. 258
13.6%
1 130
 
6.9%
3 116
 
6.1%
4 110
 
5.8%
0 105
 
5.5%
8 103
 
5.4%
5 100
 
5.3%
: 86
 
4.5%
_ 86
 
4.5%
Other values (4) 196
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 602
 
9.3%
t 516
 
8.0%
a 430
 
6.7%
s 344
 
5.3%
i 344
 
5.3%
o 344
 
5.3%
p 258
 
4.0%
c 258
 
4.0%
. 258
 
4.0%
g 258
 
4.0%
Other values (23) 2838
44.0%

_links_self
Text

UNIQUE 

Distinct184
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:08.748308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters7176
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2575561
2nd rowhttps://api.tvmaze.com/episodes/2575562
3rd rowhttps://api.tvmaze.com/episodes/2443145
4th rowhttps://api.tvmaze.com/episodes/2443146
5th rowhttps://api.tvmaze.com/episodes/2424821
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2575561 1
 
0.5%
https://api.tvmaze.com/episodes/2410540 1
 
0.5%
https://api.tvmaze.com/episodes/2443007 1
 
0.5%
https://api.tvmaze.com/episodes/2443145 1
 
0.5%
https://api.tvmaze.com/episodes/2443146 1
 
0.5%
https://api.tvmaze.com/episodes/2424821 1
 
0.5%
https://api.tvmaze.com/episodes/2417610 1
 
0.5%
https://api.tvmaze.com/episodes/2440095 1
 
0.5%
https://api.tvmaze.com/episodes/2445344 1
 
0.5%
https://api.tvmaze.com/episodes/2440050 1
 
0.5%
Other values (174) 174
94.6%
2023-08-05T14:16:09.115262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 736
 
10.3%
p 552
 
7.7%
s 552
 
7.7%
e 552
 
7.7%
t 552
 
7.7%
o 368
 
5.1%
a 368
 
5.1%
i 368
 
5.1%
. 368
 
5.1%
m 368
 
5.1%
Other values (16) 2392
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4600
64.1%
Other Punctuation 1288
 
17.9%
Decimal Number 1288
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 552
12.0%
s 552
12.0%
e 552
12.0%
t 552
12.0%
o 368
8.0%
a 368
8.0%
i 368
8.0%
m 368
8.0%
h 184
 
4.0%
d 184
 
4.0%
Other values (3) 552
12.0%
Decimal Number
ValueCountFrequency (%)
2 283
22.0%
4 276
21.4%
5 132
10.2%
3 116
9.0%
1 112
 
8.7%
9 88
 
6.8%
6 77
 
6.0%
0 74
 
5.7%
7 70
 
5.4%
8 60
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 736
57.1%
. 368
28.6%
: 184
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4600
64.1%
Common 2576
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 736
28.6%
. 368
14.3%
2 283
 
11.0%
4 276
 
10.7%
: 184
 
7.1%
5 132
 
5.1%
3 116
 
4.5%
1 112
 
4.3%
9 88
 
3.4%
6 77
 
3.0%
Other values (3) 204
 
7.9%
Latin
ValueCountFrequency (%)
p 552
12.0%
s 552
12.0%
e 552
12.0%
t 552
12.0%
o 368
8.0%
a 368
8.0%
i 368
8.0%
m 368
8.0%
h 184
 
4.0%
d 184
 
4.0%
Other values (3) 552
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 736
 
10.3%
p 552
 
7.7%
s 552
 
7.7%
e 552
 
7.7%
t 552
 
7.7%
o 368
 
5.1%
a 368
 
5.1%
i 368
 
5.1%
. 368
 
5.1%
m 368
 
5.1%
Other values (16) 2392
33.3%
Distinct122
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T14:16:09.336189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.967391
Min length31

Characters and Unicode

Total characters6250
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)49.5%

Sample

1st rowhttps://api.tvmaze.com/shows/55724
2nd rowhttps://api.tvmaze.com/shows/55724
3rd rowhttps://api.tvmaze.com/shows/59484
4th rowhttps://api.tvmaze.com/shows/59484
5th rowhttps://api.tvmaze.com/shows/64267
ValueCountFrequency (%)
https://api.tvmaze.com/shows/53242 8
 
4.3%
https://api.tvmaze.com/shows/67267 6
 
3.3%
https://api.tvmaze.com/shows/65894 6
 
3.3%
https://api.tvmaze.com/shows/50102 6
 
3.3%
https://api.tvmaze.com/shows/58000 5
 
2.7%
https://api.tvmaze.com/shows/65712 5
 
2.7%
https://api.tvmaze.com/shows/70186 4
 
2.2%
https://api.tvmaze.com/shows/65471 4
 
2.2%
https://api.tvmaze.com/shows/65504 3
 
1.6%
https://api.tvmaze.com/shows/65862 3
 
1.6%
Other values (112) 134
72.8%
2023-08-05T14:16:09.702393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 736
 
11.8%
s 552
 
8.8%
t 552
 
8.8%
h 368
 
5.9%
p 368
 
5.9%
a 368
 
5.9%
o 368
 
5.9%
. 368
 
5.9%
m 368
 
5.9%
e 184
 
2.9%
Other values (16) 2018
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4048
64.8%
Other Punctuation 1288
 
20.6%
Decimal Number 914
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 552
13.6%
t 552
13.6%
h 368
9.1%
p 368
9.1%
a 368
9.1%
o 368
9.1%
m 368
9.1%
e 184
 
4.5%
w 184
 
4.5%
c 184
 
4.5%
Other values (3) 552
13.6%
Decimal Number
ValueCountFrequency (%)
6 162
17.7%
5 137
15.0%
4 102
11.2%
2 97
10.6%
1 84
9.2%
7 73
8.0%
0 70
7.7%
3 69
7.5%
8 65
7.1%
9 55
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/ 736
57.1%
. 368
28.6%
: 184
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4048
64.8%
Common 2202
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 736
33.4%
. 368
16.7%
: 184
 
8.4%
6 162
 
7.4%
5 137
 
6.2%
4 102
 
4.6%
2 97
 
4.4%
1 84
 
3.8%
7 73
 
3.3%
0 70
 
3.2%
Other values (3) 189
 
8.6%
Latin
ValueCountFrequency (%)
s 552
13.6%
t 552
13.6%
h 368
9.1%
p 368
9.1%
a 368
9.1%
o 368
9.1%
m 368
9.1%
e 184
 
4.5%
w 184
 
4.5%
c 184
 
4.5%
Other values (3) 552
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 736
 
11.8%
s 552
 
8.8%
t 552
 
8.8%
h 368
 
5.9%
p 368
 
5.9%
a 368
 
5.9%
o 368
 
5.9%
. 368
 
5.9%
m 368
 
5.9%
e 184
 
2.9%
Other values (16) 2018
32.3%

summary
Text

MISSING 

Distinct83
Distinct (%)100.0%
Missing101
Missing (%)54.9%
Memory size1.6 KiB
2023-08-05T14:16:10.018101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length657
Median length207
Mean length225.49398
Min length32

Characters and Unicode

Total characters18716
Distinct characters84
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row<p>Dong Baek begins a new job but is surprised to learn that on his first day he has already been reassigned to the secretary department where he begins working closely with Min Yu Dam.</p>
2nd row<p>Director Min reveals that he has been waiting for Dong Baek for 300 years and that the two must begin dating. </p>
3rd row<p>One day, Seon Heo and Mu Yeong go outside to work together, but in an unexpected twist, Mu Yeong sees Seon Heo and an editor going to a hotel together.</p>
4th row<p>Seeing that Jung Woo is about to start a new life, Jung Hyun decides to reveal a long-kept secret.<br /> </p>
5th row<p>Jung Hyun and Tae Young try their best to figure out a way of getting Jung Woo back into the publishing industry, does their plan succeed by the end?<br /> </p>
ValueCountFrequency (%)
the 173
 
5.6%
to 122
 
3.9%
and 97
 
3.1%
a 90
 
2.9%
of 49
 
1.6%
is 46
 
1.5%
in 40
 
1.3%
with 34
 
1.1%
his 31
 
1.0%
their 27
 
0.9%
Other values (1437) 2388
77.1%
2023-08-05T14:16:10.668067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3005
16.1%
e 1734
 
9.3%
t 1270
 
6.8%
a 1199
 
6.4%
o 1084
 
5.8%
i 1033
 
5.5%
n 1013
 
5.4%
s 959
 
5.1%
r 892
 
4.8%
h 720
 
3.8%
Other values (74) 5807
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14114
75.4%
Space Separator 3014
 
16.1%
Uppercase Letter 625
 
3.3%
Other Punctuation 532
 
2.8%
Math Symbol 352
 
1.9%
Decimal Number 44
 
0.2%
Dash Punctuation 31
 
0.2%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1734
12.3%
t 1270
 
9.0%
a 1199
 
8.5%
o 1084
 
7.7%
i 1033
 
7.3%
n 1013
 
7.2%
s 959
 
6.8%
r 892
 
6.3%
h 720
 
5.1%
l 545
 
3.9%
Other values (19) 3665
26.0%
Uppercase Letter
ValueCountFrequency (%)
T 89
14.2%
S 55
 
8.8%
A 49
 
7.8%
M 43
 
6.9%
B 39
 
6.2%
W 34
 
5.4%
R 31
 
5.0%
C 31
 
5.0%
D 30
 
4.8%
H 23
 
3.7%
Other values (17) 201
32.2%
Other Punctuation
ValueCountFrequency (%)
. 181
34.0%
, 157
29.5%
/ 90
16.9%
' 66
 
12.4%
? 11
 
2.1%
" 10
 
1.9%
! 6
 
1.1%
: 5
 
0.9%
; 5
 
0.9%
& 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 12
27.3%
0 10
22.7%
1 6
13.6%
3 5
11.4%
9 4
 
9.1%
4 3
 
6.8%
7 2
 
4.5%
6 1
 
2.3%
5 1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 27
87.1%
3
 
9.7%
1
 
3.2%
Space Separator
ValueCountFrequency (%)
3005
99.7%
  9
 
0.3%
Math Symbol
ValueCountFrequency (%)
< 176
50.0%
> 176
50.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14739
78.8%
Common 3977
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1734
11.8%
t 1270
 
8.6%
a 1199
 
8.1%
o 1084
 
7.4%
i 1033
 
7.0%
n 1013
 
6.9%
s 959
 
6.5%
r 892
 
6.1%
h 720
 
4.9%
l 545
 
3.7%
Other values (46) 4290
29.1%
Common
ValueCountFrequency (%)
3005
75.6%
. 181
 
4.6%
< 176
 
4.4%
> 176
 
4.4%
, 157
 
3.9%
/ 90
 
2.3%
' 66
 
1.7%
- 27
 
0.7%
2 12
 
0.3%
? 11
 
0.3%
Other values (18) 76
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18675
99.8%
None 37
 
0.2%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3005
16.1%
e 1734
 
9.3%
t 1270
 
6.8%
a 1199
 
6.4%
o 1084
 
5.8%
i 1033
 
5.5%
n 1013
 
5.4%
s 959
 
5.1%
r 892
 
4.8%
h 720
 
3.9%
Other values (66) 5766
30.9%
None
ValueCountFrequency (%)
é 10
27.0%
  9
24.3%
è 6
16.2%
É 6
16.2%
ç 5
13.5%
Å 1
 
2.7%
Punctuation
ValueCountFrequency (%)
3
75.0%
1
 
25.0%

Interactions

2023-08-05T14:16:01.889708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:15:59.626424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.312086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.861464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.396199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.989007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:15:59.728737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.428015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.975557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.494604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:02.094912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:15:59.974694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.540641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.084110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.597288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:02.201857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.088053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.658639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.197287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.702482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:02.297698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.201367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:00.760133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.295736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:16:01.794451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-05T14:16:10.789029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
idid_embeddedseasonnumberruntimetype
id1.0000.3980.0560.123-0.1990.258
id_embedded0.3981.000-0.601-0.190-0.0470.081
season0.056-0.6011.0000.2920.0070.000
number0.123-0.1900.2921.000-0.2541.000
runtime-0.199-0.0470.007-0.2541.0000.000
type0.2580.0810.0001.0000.0001.000

Missing values

2023-08-05T14:16:02.450426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-05T14:16:02.712590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-05T14:16:02.881914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

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183228656519499https://www.tvmaze.com/episodes/2286565/mystery-science-theater-3000-s13-special-a-tribute-to-the-christmas-that-almost-wasntA Tribute to The Christmas That Almost Wasn't13NaNsignificant_special2022-12-1520:002022-12-16T01:00:00+00:00120.0Nonehttps://static.tvmaze.com/uploads/images/medium_landscape/434/1085131.jpghttps://static.tvmaze.com/uploads/images/original_untouched/434/1085131.jpghttps://api.tvmaze.com/episodes/2286565https://api.tvmaze.com/shows/19499<p>Join Jonah and the bots for a heartwarming tale about Santa and his lawyer trying to pay overdue rent on the North Pole in <i>The Christmas That Almost Wasn't</i>.</p><p>After the episode, stick around for a panel discussion with the cast, hosted by producer Matt McGinnis, recorded in front of a live studio audience.</p>